The anhedonia is differently modulated by structural covariance network of NAc in bipolar disorder and major depressive disorder

Journal Pre-proof The anhedonia is differently modulated by structural covariance network of NAc in bipolar disorder and major depressive disorder

Shaoqiang Han, Qian Cui, Xiao Wang, Yuyan Chen, Di Li, Liang Li, Xiaonan Guo, Yun-Shuang Fan, Jing Guo, Wei Sheng, FengMei Lu, Zongling He, Huafu Chen PII:

S0278-5846(19)30744-4

DOI:

https://doi.org/10.1016/j.pnpbp.2020.109865

Reference:

PNP 109865

To appear in:

Progress in Neuropsychopharmacology & Biological Psychiatry

Received date:

3 September 2019

Revised date:

11 January 2020

Accepted date:

15 January 2020

Please cite this article as: S. Han, Q. Cui, X. Wang, et al., The anhedonia is differently modulated by structural covariance network of NAc in bipolar disorder and major depressive disorder, Progress in Neuropsychopharmacology & Biological Psychiatry(2019), https://doi.org/10.1016/j.pnpbp.2020.109865

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© 2019 Published by Elsevier.

Journal Pre-proof The anhedonia is differently modulated by structural covariance network of NAc in bipolar disorder and major depressive disorder Shaoqiang Hana, Qian Cuib,c*, Xiao Wanga, Yuyan Chena, Di Lia, Liang Lia, Xiaonan Guoa, Yun-Shuang Fana, Jing Guoa, Wei Shenga, Feng-Mei Lua, Zongling Hea* ， Huafu Chena,b* a

The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, PR China b

MOE Key Lab for Neuroinformation; High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province,University of Electronic Science and Technology of China, Chengdu, 610054, PR China

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c

School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu,

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China

* Corresponding authors: Huafu Chen: [email protected]

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The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of life

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Science and technology，University of Electronic Science and Technology of China, Chengdu, China Or Qian Cui: [email protected]

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School of Public Affairs and Administration, University of Electronic Science and Technology of China, Chengdu, China Zongling He:[email protected]

The Clinical Hospital of Chengdu Brain Science Institute, School of life Science and technology，University of Electronic Science and Technology of China, Chengdu, China

Abstract During depressive episode, bipolar disorder (BD) patients share indistinguishable depression symptoms with major depressive disorder (MDD).However, whether neural correlates underlying the anhedonia, a core feature of depression, is different between BD and MDD remains unknown. To explore neural correlates underlying the anhedonia in BD and MDD, structural T1-weighted images from 36 depressed BD patients, 40 depressed MDD patients matched for depression severity and 34 health controls (HCs) were scanned. Considering the vital role of nucleus accumbens (NAc) in the anhedonia, we constructed the structural covariance network of NAc for each

Journal Pre-proof subject. Then, we explored altered structural covariance network of NAc and its interaction with the anhedonia severity in BD and MDD patients. As a result, BD and MDD patients shared decreased structural covariance of NAc connected to prefrontal gyrus, bilateral striatum extending to bilateral anterior insula. Apart from these regions, BD patients presented specifically increased structural covariance of NAc connected to left hippocampus extending to thalamus. The interaction between structural covariance network of NAc and the anhedonia severity in MDD was mainly associated anterior insula (AIC), amygdala, anterior cingulate cortex (ACC)and caudate while that in BD was mainly located in striatum and prefrontal cortex. Our

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results found that BD and MDD patients presented commonly and distinctly altered

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structural covariance network of NAc. What is more, the neural correlates underlying the anhedonia in BD and MDD might be different.

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Key words: anhedonia; structural covariance network; bipolar disorder; major

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depressive disorder

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Introduction

As a core feature of depression, the anhedonia is a multi-faceted symptom that

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includes deficits in the experience of pleasure, reduced approach-related motivated behavior, and impaired learning about rewards(Treadway and Zald, 2011b).

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Depressed BD or MDD patients have indistinguishable symptoms including the anhedonia, leading to high misdiagnosis of BD(Hirschfeld et al. , 2003, Phillips and Kupfer, 2013).Investigating the anhedonia(Harvey et al. , 2007) of depression helps to understand distinct physiological characterizations of BD and MDD patients (Leboyer et al. , 1998).However, whether the neural correlates of the anhedonia is different between BD and MDD remains unclear. The anhedonia in depression is related to aberrant rewarding processes(Keedwell et al. , 2005), reinforcement learning (Schultz, 1998) and motivated responding (Dichter et al. , 2009, Niv et al. , 2007, Pizzagalli et al. , 2009a, Treadway and Zald, 2011a) in the brain. The neural system underlying reward is well defined in humans including nucleus accumbens (NAc)(Haber and Knutson, 2009), orbitofrontal cortex(OFC), amygdala, anterior insula (AIC)and anterior cingulate cortex (ACC) (Avery et al. , 2014, DerAvakian et al. , 2012a, Heshmati and Russo, 2015, Wacker et al. , 2009). As a integral hub in the reward circuit(Heshmati and Russo, 2015, Hikosaka et al. , 2008),

Journal Pre-proof the NAc integrates different excitatory and inhibitory inputs to signal the salience of rewarding stimuli (Smith et al. , 2011).Studies have consistently found structural and functional aberrance in reward system across BD and MDD. For example, the activity of the NAc is consistently found decreased in depression (Drevets et al. , 1992, Mayberg et al. , 2000),this reduced activity of the NAc is related to altered reward function driving the anhedonia(Russo and Nestler, 2013).In addition, patients with depression present smaller gray matter volume in OFC and ACC (Caetano et al. , 2006, Drevets et al. , 1997, Lai et al. , 2000) and smaller BOLD signal changes during a reversal-learning task(Taylor Tavares et al. , 2008).BD patients display greater

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ventral striatum, OFC activation during reward anticipation (Caseras et al. , 2013,

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Robin Nusslock, 2012).Although common dimensional reward deficits in functional connectome are found across BD and MDD (Sharma et al. , 2017a), recent findings

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suggest that the neural correlates underlying the anhedonia in BD and MDD might be

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different (Alloy et al. , 2016, Whitton et al. , 2015).

Recent findings suggest reward processes are differently altered between BD and

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MDD. The abnormally elevated activity of ventrolateral prefrontal cortex during a guessing task distinguishes depressed BD patients from MDD patients (Chase et al. ,

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2013a). Ronny et al find BD patients present a lower activation in reward-related regions including NAc, thalamus compared with MDD patients during a card-guess

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paradigm (Redlich et al. , 2015).BD patients have significantly higher self-report of reward and punishment sensitivity when compared with MDD patients (Weinstock et al. , 2018).The differential abnormal activity of ACC distinguishes BD from MDD in emotional faces matching task (Bürger et al. , 2017).Apart from these findings, depression severity presents different relationship with social reward response in BD and MDD (Sharma et al. , 2016).Mounts of studies also find that structure and function of key regions in reward system are distinctly altered in BD and MDD(Han et al. , 2018, Versace et al. , 2010).The grey matter volume of amygdala is reduced in MDD while that in BD is increased (Konarski et al. , 2010).Amplitude of lowfrequency fluctuations (ALFF) of insula is higher in BD than that in MDD(Liu et al. , 2012). MDD patients present reduced nodal connectivity strength within reward system in ventral striatum, AIC and thalamus compared with MDD patients and HCs(Satterthwaite et al. , 2015).Taken together, these results suggest the neural correlates underlying the anhedonia in BD and MDD might be different. The

Journal Pre-proof anhedonia in BD is hypothesized to arise due to elevated activity in ventral striatum and prefrontal cortex, reflecting heighted reward sensitivity(Depue and Iacono, 2003), while that in MDD is related to altered incentive salience, incentive motivation and reinforcement learning in MDD (Alloy, Olino, 2016, Whitton, Treadway, 2015). However, there is no direct evidence to prove these hypotheses. This study, to our knowledge, was the first time to directly explore distinct neural correlates underlying the anhedonia in BD and MDD. Focusing on the NAc, a region plays a vital role in the anhedonia of depression(Cooper et al. , 2018, DerAvakian,

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Andre, 2012a, Gabbay et al. , 2013, Heshmati and Russo, 2015, Philip, 2008), the structural covariance network of NAc was constructed. Then, we explored altered

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structural covariance network of NAc and its interaction with the anhedonia severity in BD and MDD. Based on current literature, two main hypotheses were proposed.

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First, BD and MDD patients presented commonly and distinctly altered structural

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covariance network of NAc. Second, the interaction between the structural covariance network of NAc and the anhedonia severity in BD and MDD would present different

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dimensional distribution. The anhedonia in MDD might be mainly located in regions in salience network and responding for reinforcement learning, while that in BD

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might be mainly located in striatum and frontal gyrus.

Materials and methods Participants

Thirty six BD patients and 40 MDD patients were recruited from the Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China. Each patient was interviewed by two experienced psychiatrists using the Structured Clinical Interview for DSM-IV-TR-Patient Edition (SCID-P, 2/2001 revision), and was finally diagnosed to BD or MDD according to DSM-IV.The 24items Hamilton Depression scale (HAMD) was used to evaluate the clinical depressive states of the patients. All BD and MDD patients were under depressive state in this study. Exclusion criteria of patients included schizophrenia, mental retardation, personality disorder, any history of loss of consciousness, substance abuse, serious medical and neurological illness. In addition, patients were excluded if they

Journal Pre-proof were diagnosed with anxiety disorder at the same time. MDD patients were treated with antidepressants including the selective serotonin and serotonin-norepinephrine reuptake inhibitors and BD patients were treated with antidepressants, mood stabilizer and antipsychotics. The details were presented in Table 1. Thirty four healthy controls( HCs) were recruited from the community through poster advertisement. HCs were interviewed using SCID (nonpatient edition). None of them presented a history of serious medical or neuropsychiatric illness or a family history of major psychiatric or neurological illness in their first-degree relatives. HCs were

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closely matched in terms of age, gender, and years of education with the patient group. Snaith-Hamilton Pleasure Scale(SHAPS)(Franken et al. , 2007) was used to assess the

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anhedonia severity of subjects (both patients and HCs). We also calculated total

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medication load to account for the effect of different medications(Han et al. , 2019c,

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Redlich et al. , 2014, Redlich, Dohm, 2015).

Written informed consents were obtained from all participants before experiment. The

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study was approved by the research ethical committee of University of Electronic

Scan acquisition

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Science and Technology of China.

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Data were acquired on a 3-Tesla GE Discovery MR750 scanner (General Electric, Fairfield Connecticut, USA). Using a 8-channel prototype quadrature birdcage head coil, we acquired structural T1-weighted images with 3D spoiled gradient echo scan sequence: TR/TE = 5.92/1.956 ms, voxel size = 1 mm × 1 mm × 1 mm, slice thickness = 1 mm, no gap, flip angle = 12°, matrix size = 256 × 256, and 156 slices. Voxel Based Morphometry Analysis All scans were processed using the VBM8.0 toolbox (http://dbm.neuro.unijena.de/vbm.html). The stand pipline steps were used including1).Bias-field correction.2).Segmentation(gray and white matter and cerebrospinal fluid).3), Adjustment for partial volume effects.4). Normalization into Montreal Neurological Institute space.5).Nonlinear modulation (22). Definition of NAc

Journal Pre-proof To determine the coordinate of NAc, we searched the meta analysis results from Neurosyth(http://neurosynth.org/) using “reward” as search term. The bilateral peak coordinates of NAc( MNI coordination : ±16, 12, -4 )were selected in uniformity test map(sFigure 1). The region of interest (ROI) was defined with spherical radius of 3.5 mm (sFigure 2). Statistical Analyses The following steps were performed using SurfStats toolbox for Matlab(Worsley et

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al. , 2009).

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Altered structural covariance network of NAc in BD and MDD patients To explore altered covariance structural network of NAc in BD and MDD, the

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following model was used:

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Vi   0   1 * Sex   2 * Age   3*Edu   4 *Vseed

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where Vi was the gray matter volume of voxel i , Vseed was the mean gray matter volume of ROI. Age, sex and year of education were treated as covariates. Then the

 was compared between BD (or MDD) patients with HCs, between BD and MDD

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patients using two tailed two sample t test.

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Results were corrected for multiple comparison (voxel-wise p < 0.005, cluster-level p < 0.05; Gaussian random field (GRF) corrected)(Han et al. , 2019a). Overlapping abnormalities in BD and MDD patients In previous step, we separately explored altered structural covariance networks in BD and MDD patients. To quantify the degree of overlapping abnormalities in BD and MDD patients, the Dice coefficient of similarity (DCS) was used (Han et al. , 2019b, Zou et al. , 2004). DCS was calculated between BD and MDD patients of significant differences (voxel-wise p < 0.005, cluster-level p < 0.05; GRF corrected). DSC(A,B) =2(A∩ B)/(A + B) where ∩ is the intersection. A higher DCS value means that BD and MDD have a higher degree of overlapping(a DCS value of 100% means perfect spatial agreement in the distribution of abnormalities) (Zou, Warfield, 2004).

Journal Pre-proof Interaction between structural covariance network of NAc and the anhedonia in BD and MDD patients To assess interaction between structural covariance network of NAc and the anhedonia severity in BD and MDD, we fitted interaction models that include mean gray matter volume of ROI, SHAPS score, and their parametric interaction. Vi   0   1 * Sex   2 * Age   3*Edu   4*Score   5*Vseed   6 *Vseed*Score

where * denotes an interaction. A positive interaction indicates higher structural covariance in individuals with higher scores; a negative interaction suggests a weaker

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link. Two tails one sample t test of  6 was conducted in BD (or MDD) patients. Results were corrected for multiple comparison (voxel-wise p < 0.005, cluster-level p

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< 0.05; Gaussian random field (GRF) corrected)(Han, He, 2019a).

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Validation

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To excluded the effect of medicine, we calculated interaction between structural covariance network of NAc and medicine load in BD and MDD patients. In addition ,

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the Pearson's correlation coefficient between medicine load and the anhedonia

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severity was also calculated.

Clinical effects

Demographic and clinical characteristics of subjects were shown in Table 1. Sociodemographic characteristics including age, gender, years of education presented no significant difference among three groups (Table 1).There was no significant difference of HAMD between BD and MDD. Both BD (p < 0.01)and MDD (p < 0.01) presented higher SHAPS score than HCs, while there was no significant difference of SHAPS score between BD and MDD patients (p > 0.99). Structural covariance network of NAc was differently altered in BD and MDD patients

Journal Pre-proof The structural covariance of NAc connected to the bilateral striatum (including putamen and caudate) extending to bilateral anterior insula, medial orbitofrontal cortex(mOFC), dorsolateral prefrontal cortex(DLPFC) ,superior temporal gyrus and cerebellum was decreased in BD patients. While, the structural covariance of NAc connected to the left hippocampus extending to thalamus was increased in BD patients (Figure 1, Table S1). On the other hand, MDD patients presented overall decreased structural covariance of NAc connected to the bilateral striatum (including putamen and caudate) extending to

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bilateral AIC, OFC, middle temporal gyrus, inferior temporal, right hippocampus extending to parahippocampal gyrus(Figure 1, sTable 1).

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The DCS value of altered structural covariance of NAc in BD and MDD was 47.08 %.

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We also compared structural covariance network of NAc between BD and MDD

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patients. Compared with MDD patients , BD patients presented increased structural covariance of NAc connected toleft inferior prefrontal gyrus, left AIC extending to

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inferior prefrontal cortex (triangular part)and left ACC while decreased structural covariance of NAc connected to left thalamus (Figure 1, sTable 1).

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Figure 1.

Structural covariance network of NAc underlying the anhedonia in BD and MDD patients

Then, we explored the different interaction between structural covariance network of NAc and the anhedonia severity in BD and MDD patients. Both BD and MDD presented significant interaction between structural covariance network of NAc and the anhedonia severity. However, the significant interaction presented different dimensional distribution in BD and MDD. Specially, the positive interaction between structural covariance of NAc and the anhedonia severity was mainly located in frontal gyrus including inferior OFC, left ACC, left inferior frontal gyrus (triangular part). The negative interaction was in left striatum and cerebellum. On the other hand, MDD presented significantly positive interaction in right parahippocampal gyrus extending to amygdala, right precentral

Journal Pre-proof gyrus and right AIC and negative interaction in right caudate, inferior temporal gyrus , ACC and cerebellum (Figure2, sTable 2). Validation There was no significant interaction between structural covariance network of NAc and medicine load in BD and MDD patients (voxel-wise p < 0.005, cluster-level p < 0.05; Gaussian random field (GRF) corrected). The correlation between medicine load

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and the anhedonia severity was not significant (p > 0.05).

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Figure 2.

Discussion

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To our knowledge, it was the first time to directly explore the different neural basis underlying the anhedonia in BD and MDD patients. There were two main findings in

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this study. First, structural covariance network of NAc was differently altered between BD and MDD. Especially, the structural covariance of NAc connected to

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regions including left hippocampus and thalamus, presented opposite differences in BD and MDD. Second, the interaction between structural covariance network of NAc and the anhedonia severity presented different dimensional distribution in BD and MDD. Specifically speaking, the neural basis underlying the anhedonia in MDD might be more related to blunted processing of incentive salience, weak reward source memory and reinforcement learning, while that in BD was mainly related to structural covariance network of NAc connected to OFC and striatum. We found commonly and distinctly altered structural covariance network of NAc and its specific role in the anhedonia in BD and MDD. BD and MDD shared decreased structural covariance of NAc connected to regions playing import roles in reward circuit including dopamine related subcortical regions, AIC and prefrontal cortex. Previous studies consistently found altered reward deficits in BD and MDD (Sharma et al. , 2017b, Singh et al. , 2018). For example, the altered

Journal Pre-proof functional connectivity of NAc connected to the bilateral insula, a central hub of reward processes, was found in patients with depression (Camara et al. , 2009). Being linked to the processing of both gain and loss and to reward-related decision making (Camara, Rodriguez-Fornells, 2009), the function connectivity of AIC connected to NAc was observed across psychiatric disorders (Sharma, Wolf, 2017b) representing a transdiagnostic early marker of reward dysfunction (Singh, Leslie, 2018). The hippocampus receiving and sending inputs to key brain regions in reward circuit, played an important role in processing of reward valence (Richardson et al. , 2004, Yonelinas et al. , 2015). In addition, the dysfunction of OFC, in charge of experiences

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of pleasure, subjective assessments of pleasure and reward evaluate (DerAvakian et

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al. , 2012b, Rolls et al. , 2015), was consistently observed to be related to altered reward processing in depression (Cheng et al. , 2016, Cotter et al. , 2015, Dillon et al. ,

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2014, Macoveanu et al. , 2014, Riaz et al. , 2017, Rolls, 2017). In line with these studies, we found decreased structural covariance of NAc connected to these regions

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in both BD and MDD suggesting commonly altered reward processes in BD and

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MDD.

Although sharing altered structural covariance network of NAc, BD presented distinct

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aberrance compared with MDD. Overall, the DCS value of altered structural covariance of NAc was 47.08 % suggesting that the degree of overlapping

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abnormalities was limited in BD and MDD. Specially, the structural covariance of NAc connected to regions including left hippocampus and thalamus, presented opposite differences in BD and MDD. These regions were reported to be decreased activation in reward condition in the BD patients compared with MDD patients (Redlich, Dohm, 2015).Our previous study(Han, He, 2019a),also found that functional connectivity of subcortical regions including thalamus and hippocampus connected to the raphe nuclei presented opposite difference in BD and MDD patients when compared with HCs suggesting the different serotonergic disruption in BD and MDD. Another regions like ACC, its resting cerebral blood flow presented good discernment BD from MDD patients(Almeida et al. , 2013, Bertocci et al. , 2012, Lamm and Singer, 2010). Combing with these evidences, our results affirmed differently altered reward processes in BD and MDD. Most important of all, we found interaction between structural covariance network of NAc and the anhedonia severity presented different dimensional distribution in BD

Journal Pre-proof and MDD. These results suggested neural correlates underlying the anhedonia were different in BD and MDD. Although BD shared indistinguishable the anhedonia symptoms with MDD, the neural correlates of the anhedonia were hypothesized to be different(Whitton, Treadway, 2015). The anhedonia in MDD was more related to blunted processing of incentive salience, weak reward source memory and reinforcement learning(Alloy, Olino, 2016, Whitton, Treadway, 2015). For example, prediction error with reinforcement learning theories was hypothesized underlie the anhedonia in depression(Gradin et al. , 2011). Reduced reward-learning signals implied reduced salience to rewarding events(Kumar et al. , 2008) then followed by

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reduced ability to modulate behavior as a function of rewards(Pizzagalli et al. , 2009b,

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Vrieze et al. , 2013). In addition, previous studies found many regions was involved into the encoding of prediction errors including striatum(O'Doherty et al. , 2004),

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amygdala(Kumar, Waiter, 2008)whose connection to NAc contributed to reward seeking(Christoffel et al. , 2015, Porcelli et al. , 2012, Stuber et al. , 2011)and

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insula(Waltz et al. , 2009)playing an important role in motivated decision making(Treadway et al. , 2012). Dysfunction of these regions might result in

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inefficient responsiveness to rewards in MDD(Alloy, Olino, 2016, Whitton, Treadway, 2015).In line with these evidences, we found that the anhedonia severity was

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modulated by structural covariance of NAc connected to frontal gyrus, ACC and striatum, providing a direct evidence for this hypothesis. On the other hand, the

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anhedonia in BD was mainly located in frontal gyrus and striatum. These results were consistent with reward hypersensitivity theory originally proposed by Depue and Iacono(Depue and Iacono, 2003). Abnormally elevated reward sensitivity as a risk factor for BD(Alloy et al. , 2015, Johnson et al. , 2012). The elevated reward sensitivity might be resulted from elevated activity within the dopamine-rich NAc and a failure of prefrontal regions to effectively down-regulate ventral striatum responses(Damme et al. , 2017, Dillon, Dobbins, 2014, Trost et al. , 2014a, Whitton, Treadway, 2015). When BD patients experienced reward system deactivating or activating environmental events, their reward systems became too strongly deactivated or activated, resulting into depression, hypomania or mania (Alloy, Olino, 2016). There were mounts of evidences supporting this hypothesis(Alloy, Olino, 2016). For example, BD patients exhibited greater ventral striatum, OFC activation during reward anticipation (Caseras, Lawrence, 2013, Robin Nusslock, 2012)and these abnormally elevated activity could distinguish depressed BD patients from

Journal Pre-proof depressed MDD patients(Chase et al. , 2013b). A failure of prefrontal regions to effectively down-regulate ventral striatum responses was observed (Trost et al. , 2014b) in depressed BD patients. In line with this hypothesis, our results found that the neural correlates of the anhedonia might be related to reward hypersensitivity in BD. Taken together, different dimensional distribution in BD and MDD suggested that the neural correlates underlying the anhedonia in BD and MDD was different. To our knowledge, it was the first time to directly explore the different neural basis underlying the anhedonia in BD and MDD patients. Our results provided new direct

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evidences for this hypothesis. There were a number of limitations in the current study. First, most patients (both BD

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and MDD) were treated with medications. Second, our results were based on a single dataset with limited sample size. Future study was expected to use medication-free

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Conclusion

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large samples to validate our results.

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This was the first study to explore the different neural basis underlying the anhedonia in patients with BD and MDD. BD and MDD patients not only presented commonly

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and distinctly abnormal structural covariance network of NAc, the interaction between the structural covariance network of NAc and the anhedonia severity

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presented different dimensional distribution in BD and MDD. Our results provided direct evidences that the neural correlates underlying the anhedonia in BD and MDD was different.

Acknowledgments

This work was supported by the Natural Science Foundation of China (61533006, U1808204,81771919), Key Project of Research and Development of Ministry of Science and Technology (2018AAA0100705),the Scientific research project of Sichuan Medical Association (S15012), the Youth Innovation Project of Sichuan Provincial Medical Association (Q14014),China Postdoctoral Science Foundation Grant (Grant No. 2019M653383). Financial disclosures All authors declared no conflict of interest.

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Journal Pre-proof Table 1. Demographic and Clinical Characteristics of subjects. BD (n=36)

MDD (n=40)

HC (n=34)

p

Age (years), mean ± SD

33.39 ± 10.16

33±10.71

30.85 ± 9.73

0.54a

Gender, male: female

20:16

18:22

18:16

0.65b

Years of education, mean ±

13.86 ± 3.00

14.53 ± 3.49

13.70 ± 3.11

0.51a

Handedness, right/left

35 / 1

40 / 0

33 / 1

0.56 a

Age of first onset (years)

36.42 ± 8.73

28.30 ± 9.93

-

0.39c

No. of depression episodes

1.58 ± 1.05

2.07 ± 1.10

-

>0.05c

Duration of single

2.17 ± 1

3.23 ± 1.97

-

<0.01c

23.08 ± 4.80

-

0.03 c

2.18 ± 0.92

-

<0.01c

28.73 ± 6.18

23.85 ± 6.16

<0.01a

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of

SD

20.14 ± 6.85

Medicine load

3.14 ± 1.33

SHAPS

28.72 ± 5.41

Fluoxetine

lP

(Number of patients)

na

Antidepressants

re

HAMD

-p

depressiveepisode

1

2

9

9

Paroxetine

6

25

Escitalopram

0

0

Fluvoxamine

0

0

Venlafaxine

2

6

Duloxetine

1

4

Mirtazapine

0

1

Valproate

22

1

Lamotrigine

1

0

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Sertraline

Mood stabilizer

Journal Pre-proof Lithium

5

0

Olanzapine

8

7

Quetiapine

17

11

Risperidone

2

2

Aripiprazole

1

1

Antipsychotics

Note: a one -way ANOVA, bChi-square t-test, c two-tailed two sample t test; HC, healthy control; MDD, major depressive disorder; BD, bipolar disorder;HAMD, Hamilton Depression scale;

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SHAPS, Snaith-Hamilton Pleasure Scale.

Journal Pre-proof Figure 1. Differently altered structural covariance network of NAc in BD and MDD.

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The DCS value meant the degree of overlapping abnormalities in BD and MDD.

Journal Pre-proof Figure 2. The interaction of structural covariance network of NAc underlying the

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anhedonia in BD and MDD.

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The study was approved by the research ethical committee of University of Electronic Science and Technology of China.

Journal Pre-proof Authors' contributions Shaoqiang Han mainly write the paper. Shaoqiang Han, Xiao Wang, Liang Li, Wei Sheng are charge of designing the method. Yuyan Chen, Di Li, Zongling He, Xiaonan Guo, Yun-Shuang Fan, Jing Guo are in charge of data acquisition. Qian Cui and Huafu Chen design all study. The manuscript is revised by all authors and the final

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version of manuscript is approved by all authors.

Journal Pre-proof Disclosure statement This is an original manuscript and no parts of this manuscript are being considered for publication elsewhere. All authors have approved this manuscript. No author has

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financial or other contractual agreements that might cause conflicts of interest.

Journal Pre-proof It is the first time to directly explore the different neural basis underlying the anhedonia in BD and MDD patients.



BD and MDD patients present commonly and distinctly abnormal structural covariance network of NAc, the interaction between the structural covariance network of NAc and the anhedonia severity present different dimensional distribution in BD and MDD.



Our results provid direct evidences that the neural correlates underlying the anhedonia in BD and MDD might be different.

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

Figure 1

Figure 2